A new load cell-based Weight-in-Motion (WIM) equipment for detecting traffic overload conditions on the roadway structure is proposed. The system consists of two load detection sensors, a supporting and stiffening steel structure, a reinforced concrete (RC) basement, and a steel covering plate. Embedded within the road pavement at grade with the top asphalt surface, the sensors are offset to avoid missing values while gathering the data from the passing vehicle. This strategy ensures the passage of both the axle’s wheels through the measuring area, which is the top surface of a steel beam supported by four load cells. Being the beam width smaller than the wheel’s contact surface, a tailored algorithm has been implemented to process the gathered data and return the Gross Vehicle Weight (GVW). More than 500 experimental tests have been performed to assess the system’s performance. A relatively rigid basement reduces the noise related to the vibrations generated by the system itself, which might affect the data analysis. Nonlinear dynamical FE analyses have been performed to support the structural design. A reduction in operating costs is allowed by the streamlined low-maintenance configuration of the system, along with its robustness.
Weight-in-Motion System for Traffic Overload Detection: Development and Experimental Testing
Di Giacinto D.;Laudante G.;Grassia L.;Ruocco E.
2021
Abstract
A new load cell-based Weight-in-Motion (WIM) equipment for detecting traffic overload conditions on the roadway structure is proposed. The system consists of two load detection sensors, a supporting and stiffening steel structure, a reinforced concrete (RC) basement, and a steel covering plate. Embedded within the road pavement at grade with the top asphalt surface, the sensors are offset to avoid missing values while gathering the data from the passing vehicle. This strategy ensures the passage of both the axle’s wheels through the measuring area, which is the top surface of a steel beam supported by four load cells. Being the beam width smaller than the wheel’s contact surface, a tailored algorithm has been implemented to process the gathered data and return the Gross Vehicle Weight (GVW). More than 500 experimental tests have been performed to assess the system’s performance. A relatively rigid basement reduces the noise related to the vibrations generated by the system itself, which might affect the data analysis. Nonlinear dynamical FE analyses have been performed to support the structural design. A reduction in operating costs is allowed by the streamlined low-maintenance configuration of the system, along with its robustness.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
